Web services that serve as content providers, such as search engines, social networks, and media outlets, often utilize recommender systems that tailor content for a user. For example, a recommender system may tailor content for a user by providing advertisements, search results, articles, and/or other content that pertains to a user's interests, demographic, or other preferences.
While tailoring content can be useful to filter large amounts of general information, recommender systems can also create a “content bubble”, where a user's requests for information are consistently fulfilled with non-diverse, personalized responses. Content bubbles may, therefore, limit a user's exposure to diverse content, such as content that pertains to alternative viewpoints and topics, even when such diverse content may be of interest to the user.